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Software . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
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Impresso Datalab - News Agencies Recognition and Linking with Impresso BERT models

Authors: Boros, Emanuela; Mello, Caio;

Impresso Datalab - News Agencies Recognition and Linking with Impresso BERT models

Abstract

The Impresso project processes large collections of media archives and develops the Impresso Web App and Datalab for their exploration. In the context of the Impresso Datalab, this notebook demonstrates how to find mentions of news agencies in historical newspaper articles by loading a pre-trained model from Hugging Face. The model, part of the Impresso Project, is designed to recognize agency names such as Reuters, AFP, Havas, or DPA in texts written in French and German.

Keywords

impresso datalab, Newspapers as Topic, history, impresso project, Newspapers as Topic/history, Digital humanities

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average